Admittedly, this header is somewhat misleading: given the enormity of Python, it’s more challenging to get this section correct than coding SuPy per se. As such, here a collection of data analysis oriented links to useful Python resources is provided to help novices start using Python and then SuPy.

The gist of Python: a quick introductory blog that covers Python basics for data analysis.

Jupyter Notebook: Jupyter Notebook provides a powerful notebook-based data analysis environement that SuPy users are strongly encouraged to use. Jupyter notebooks can run in browsers (desktop, mobile) either by easy local configuration or on remote servers with pre-set environments (e.g., Google Colaboratory, Microsoft Azure Notebooks). In addition, Jupyter notebooks allow great shareability by incorporating source code and detailed notes in one place, which helps users to organise their computation work.

Installation

Jupyter notebooks can be installed with pip on any desktop/server system and open .ipynb notebook files locally: